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Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 6:50 am
by nschmidt
I'd push back on this a bit. Robotics engineers in the US were reportedly seeing $150k-$205k total comp at mid-level and $205k-$300k at senior level in 2026, with humanoid- and foundation-model-specialist roles clearing $280k-$475k - a meaningful premium over general robotics/automation roles.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by garcia51
@nschmidt This matches what I've seen too. Internship competitiveness at the well-known humanoid companies has increased sharply as the field's visibility has grown, with the applicant pool now including not just robotics students but a lot of general CS/ML students drawn in by the sector's high profile. A whole-body control engineer's day-to-day work is a mix of formulating and tuning constrained optimization problems, debugging why a controller behaves differently on hardware than in simulation, and a surprising amount of time spent on numerical stability and solver performance rather than pure algorithm design.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by emily45
@garcia51 Slight correction, though the overall point stands: 24/7 factory-pilot support roles (the engineers keeping a deployed fleet running through real shifts) reportedly carry a real burnout risk, since they combine the unpredictability of early-stage hardware with the operational pressure of a live production environment. Transitioning from industrial automation into humanoid-specific roles is a increasingly common and viable path, since a lot of the underlying skills (motion control, safety systems, real-time software) transfer directly, even though the specific dynamics and learned-control components are new. Reminds me a bit of the early drone hobbyist scene, honestly.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by amandawhite
@emily45 Speaking from personal experience here, The common academic path into this field is a master's or conversion course in robotics or machine learning, followed by an internship or research role at a known lab or company - a PhD is common but increasingly not strictly required for industry roles, especially on the applied engineering side.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by brenda52
@amandawhite I can speak to this a bit. Remote work remains genuinely limited for most hands-on humanoid hardware roles, given the need for physical access to robots and test environments, though software-only roles (simulation, perception algorithms, offline learning) increasingly do offer remote or hybrid arrangements. Robotics engineers in the US were reportedly seeing $150k-$205k total comp at mid-level and $205k-$300k at senior level in 2026, with humanoid- and foundation-model-specialist roles clearing $280k-$475k - a meaningful premium over general robotics/automation roles. Reminds me a bit of the early drone hobbyist scene, honestly.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by ethan_fisc
Counterpoint: A strong, well-documented personal project (even a modest DIY build or a solid simulation-based RL project) reportedly carries real weight in hiring for this field, partly because the field is young enough that a demonstrated hands-on track record can meaningfully substitute for a less-relevant formal credential. Robotics engineers in the US were reportedly seeing $150k-$205k total comp at mid-level and $205k-$300k at senior level in 2026, with humanoid- and foundation-model-specialist roles clearing $280k-$475k - a meaningful premium over general robotics/automation roles. Kind of makes me think about how different this all looked even three years ago.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by barbara_liu
@ethan_fisc From what I've seen: Internship competitiveness at the well-known humanoid companies has increased sharply as the field's visibility has grown, with the applicant pool now including not just robotics students but a lot of general CS/ML students drawn in by the sector's high profile.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by rossi30
Just to be precise about one thing: A commonly cited skill gap in new-grad applicants is practical systems integration experience - many candidates are individually strong in ML or in mechanical design, but comparatively few have hands-on experience getting perception, planning, and control to work together reliably on real hardware under time pressure.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by sven.smith4
@rossi30 This lines up with my experience. Remote work remains genuinely limited for most hands-on humanoid hardware roles, given the need for physical access to robots and test environments, though software-only roles (simulation, perception algorithms, offline learning) increasingly do offer remote or hybrid arrangements.

Re: Anyone changed specialization mid-career (e.g. perception to controls) - how hard was it?

Posted: Sun Aug 30, 2026 11:59 am
by aliu
This is exactly the kind of context I was looking for. In the UK, base salaries for robotics roles reportedly range from around £50,000 for new graduates up to roughly £200,000 for senior whole-body-control or reinforcement-learning specialists - a notably wide band reflecting how specialized the top end of the field has become. RSS (Robotics: Science and Systems), ICRA, and the IEEE-RAS Humanoids conference are commonly cited as the most directly relevant venues for someone specifically interested in legged locomotion and humanoid control research, as opposed to broader AI/ML conferences.